The preliminary results reported in tab:accuracycifar10bnn show that ASkewSGD is state-of-the art for training BNNs with binary weights and activations. Activation with the function \(\operatorname{sign(\cdot )}\)  leads to a loss in expressive power and consequently a loss in performance. Several works introduce additional tricks such as real scaling factors [1]} to bridge the gap between binary signals and their real counterparts. These tricks can be easily implemented in our approach ASkewSGD. 